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We report on a curriculum development project in which students explore environmental racism through data. Recognizing that quantitative data alone is insufficient to understand the sociohistorical contexts of racism, we draw from syncretic approaches to learning that put everyday experiences and qualitative evidence into direct conversation with quantitative datasets through storytelling. Through two focal cases, we demonstrate how one student leveraged personal experience to engage in deep integrative analysis of data, while another with fewer perceived personal connections to environmental racism focused more specifically on patterns, with less structural or racial analysis. Implications of the analysis include the need to carefully attend to the use of quantitative data related to race and to scaffold the integration of other sources of information with quantitative data sets.
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This content will become publicly available on March 23, 2026
Harnessing Personal Storytelling to Support Teachers’ Initial Grasp of Understanding Computational Thinking
Traditional professional development aimed at integrating computational thinking (CT) into K-12 classrooms frequently fails to link abstract technical terminology with teachers' personal experiences or real-world situations, which can impede overall teacher understanding and effective classroom implementation. This paper investigates an alternative method that employs personal storytelling to introduce CT to educators. We discovered that storytelling helped build emotional connections and prompted deeper reflections on CT concepts. Participants shared how CT appears in various settings, including teaching, parenting, and outdoor activities, which transformed their understanding and forged significant connections between theory and practice.
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- Award ID(s):
- 2219332
- PAR ID:
- 10615456
- Publisher / Repository:
- National Association for Research in Science Teaching
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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